• Phonetics and Speech Sciences
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• v.1 no.4
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• pp.119-125
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• 2009

This paper proposes fast speaker adaptation method using artificially distorted speech in telematics terminal under the car noise environment based on eigenspace-based maximum likelihood linear regression (ES-MLLR). The artificially distorted speech is built from adding the various car noise signals collected from a driving car to the speech signal collected from an idling car. Then, in every environment, the transformation matrix is estimated by ES-MLLR using the artificially distorted speech corresponding to the specific noise environment. In test mode, an online model is built by weighted sum of the environment transformation matrices depending on the driving condition. In 3k-word recognition task in the telematics terminal, we achieve a performance superior to ES-MLLR even using the adaptation data collected from the driving condition.

• Journal of Engineering Education Research
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• v.15 no.5
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• pp.25-30
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• 2012

"The engineering education program for environmental intention and value creation" has been executed from 2008 to 2010 in Suzuka National College of Technology, which program was promoted as "Good Practice for Education" by Ministry of Education, Culture, Sports, Science and Technology Japan. "Eco-car project" is one of these practical ecology/environment education programs. The project's members have been learning and researching the environmental managements by the process of design, manufacturing, and assembly of solar car, highly effective fuel consumption car (Eco-run car), electric vehicle and fuel-cell car. Also this project was supported by some professional experts of the local industries and community. The students learned the actual industrial technique, the engineering management and the structure of local industries by this project. In this paper, the environmental intention engineering design education with local industry collaboration is introduced.

• Proceedings of the KSPS conference
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• 2005.11a
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• pp.147-150
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• 2005

The performance of speech recognition in car environment is severely degraded when there is music or news coming from a radio or a CD player. Since reference signals are available from the audio unit in the car, it is possible to remove them with an adaptive filter. In this paper, we present experimental results of speech recognition in car environment using the echo canceller. For this, we generate test speech signals by adding music or news to the car noisy speech from Aurora2 DB. The HTK-based continuous HMT system is constructed for a recognition system. In addition, the MMSE-STSA method is used to the output of the echo canceller to remove the residual noise more.

• The Journal of the Acoustical Society of Korea
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• v.22 no.2E
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• pp.62-68
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• 2003

This paper addresses a novel noise-compensation scheme to solve the mismatch problem between training and testing condition for the automatic speech recognition (ASR) system, specifically in car environment. The conventional spectral subtraction schemes rely on the signal-to-noise ratio (SNR) such that attenuation is imposed on that part of the spectrum that appears to have low SNR, and accentuation is made on that part of high SNR. However, these schemes are based on the postulation that the power spectrum of noise is in general at the lower level in magnitude than that of speech. Therefore, while such postulation is adequate for high SNR environment, it is grossly inadequate for low SNR scenarios such as that of car environment. This paper proposes an efficient spectral subtraction scheme focused specifically to low SNR noisy environment by extracting harmonics distinctively in speech spectrum. Representative experiments confirm the superior performance of the proposed method over conventional methods. The experiments are conducted using car noise-corrupted utterances of Aurora2 corpus.

• MALSORI
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• no.62
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• pp.85-96
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• 2007

In this paper, we carried out recognition experiments for noisy speech having various levels of car noise and output of an audio system using the speech interface. The speech interface consists of three parts: pre-processing, acoustic echo canceller, post-processing. First, a high pass filter is employed as a pre-processing part to remove some engine noises. Then, an echo canceller implemented by using an FIR-type filter with an NLMS adaptive algorithm is used to remove the music or speech coming from the audio system in a car. As a last part, the MMSE-STSA based speech enhancement method is applied to the out of the echo canceller to remove the residual noise further. For recognition experiments, we generated test signals by adding music to the car noisy speech from Aurora 2 database. The HTK-based continuous HMM system is constructed for a recognition system. Experimental results show that the proposed speech interface is very promising for robust speech recognition in a noisy car environment.

• Journal of Digital Contents Society
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• v.10 no.1
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• pp.121-127
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• 2009

The automotive ECU(Electronic Control Unit) becomes more complicated and is demanding many functions. For example, many automobile companies are developing driver convenience systems such as power window switch, LCM(Light Control Module), mirror control system, seat memory. In addition, many researches and developments for DIS(Driver Information System) are in progress. It is dangerous to operate such systems in driving. In this paper, we implement the speech recognition system which controls the car convenience system using speech, and apply the preprocessing filter to improve the speech recognition rate in car noise environment. As a result, we get the good speech recognition rate in car noise environment.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.4
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• pp.415-421
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• 1997

A car driving trainer for beginners developed under PC-based environment is described in this paper. For this trainer, a hardware is implemented as a practice car, and a trainer program is designed by computer image generation method to display 3-dimensional images on a CRT monitor. The trainer program consists of 3 main parts, that is, a speed estimate part, a wheel trace calculation part and a driving image generation part. Furthermore, a map editor is also installed for taking any test drive. After comparing this driving trainer to specify it was verified that the developed car driving trainer showed has good performances, such as lower cost, higher resolution and better image display speed.

• Journal of Auto-vehicle Safety Association
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• v.11 no.3
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• pp.30-36
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• 2019

This paper suggests a car-following algorithm for urban environment, with multiple target candidates. Until now, advanced driver assistant systems (ADASs) and self-driving technologies have been researched to cope with diverse possible scenarios. Among them, car-following driving has been formed the groundwork of autonomous vehicle for its integrity and flexibility to other modes such as smart cruise system (SCC) and platooning. Although the field has a rich history, most researches has been focused on the shape of target trajectory, such as the order of interpolated polynomial, in simple single-lane situation. However, to introduce the car-following mode in urban environment, realistic situation should be reflected: multi-lane road, target's unstable driving tendency, obstacles. Therefore, the suggested car-following system includes both in-lane preceding vehicle and other factors such as side-lane targets. The algorithm is comprised of three parts: path candidate generation and optimal trajectory selection. In the first part, initial guesses of desired paths are calculated as polynomial function connecting host vehicle's state and vicinal vehicle's predicted future states. In the second part, final target trajectory is selected using quadratic cost function reflecting safeness, control input efficiency, and initial objective such as velocity. Finally, adjusted path and control input are calculated using model predictive control (MPC). The suggested algorithm's performance is verified using off-line simulation using Matlab; the results shows reasonable car-following motion planning.

• The Journal of the Convergence on Culture Technology
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• v.4 no.3
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• pp.227-233
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• 2018

In recent years, connected car, which has sensors and computers attached to vehicles used to detect the surrounding environment, has been actively studied. However, in order to configure the connected car environment, various sensors and roadside equipments are required to detect the surrounding environment of the vehicle, and also communication techniques for transmitting the collected data are in demands. Therefore, in this paper, the mobile virtual fence that collects and communicates the data of the surrounding environment through the sensor mounted on the mobile device is applied to the vehicles that were released before the connected car service environment was constructed, We propose a mechanism to receive the service and show the possibility through experiment.

• Journal of Information Processing Systems
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• v.20 no.2
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• pp.173-184
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• 2024

The connected car services are one of the most widely used services in the Internet of Things environment, and they provide numerous services to existing vehicles by connecting them through networks inside and outside the vehicle. However, although vehicle manufacturers are developing services considering the means to secure the connected car services, concerns about the security of the connected car services are growing due to the increasing number of attack cases. In this study, we reviewed the research related to the connected car services that have been announced so far, and we identified the threats that may exist in the connected car services through security threat modeling to improve the fundamental security level of the connected car services. As a result of performing the test to the applications for connected car services developed by four manufacturers, we found that all four companies' applications excessively requested unnecessary permissions for application operation, and the apps did not obfuscate the source code. Additionally, we found that there were still vulnerabilities in application items such as exposing error messages and debugging information.